ModuLiDAR is an all-in-one open-source software for autonomous UGVs and industrial robots.

Overview

CI

ModuLiDAR

ModuLiDAR is an all-in-one open-source software for autonomous UGVs and industrial robots. the target industries that ModuLiDAR is working on are farming industry, mining industry, warehouses industry, and construction industry.

we were always wondering why there isnt any framework that processes robust autonomous software stack on Raspberry Pi board that can be used in UGV industries, do we always need a NVIDIA board?. The result was ModuLiDAR :)

ModuLiDAR Featues

  • Modular software components can work with different sensors(benwake/velodyne)
  • 3D semantic segmentaiton object detection.
  • Freespace estimation.
  • Integration of ModuLiDAR with ROS packages such as gmapping, move base, and amcl.
  • Free space fusion for cocoon Setup.
  • 3D point cloud assembly.

ModuLiDAR Planned Features

  • 3D mapping and matching.
  • Object tracking.
  • new approaches for 2D mapping and matching.
  • DNN detection and semantic segmentation.
  • Camera-LiDAR fusion.

Demos:

Navigation

ModuLiDAR Farm simulation demo Velodyne

roslaunch gazebo_simulator robot_navigation.launch sensor:=velodyne world_name:='$(find gazebo_simulator)/worlds/turtlebot3_world.world' map_file:='$(find gazebo_simulator)/maps/map.yaml'

velo_farm

ModuLiDAR Cave simulation demo velodyne

roslaunch gazebo_simulator robot_navigation.launch sensor:=velodyne world_name:='$(find gazebo_simulator)/worlds/50m_long_mine_world.world' map_file:='$(find gazebo_simulator)/maps/mymap_cave.yaml'

velo_cave

ModuLiDAR Farm simulation demo Benwake cocoon

roslaunch gazebo_simulator robot_navigation.launch sensor:=benwake world_name:='$(find gazebo_simulator)/worlds/turtlebot3_world.world' map_file:='$(find gazebo_simulator)/maps/map.yaml'

benwake_farm

SLAM

ModuLiDAR map farm environment

roslaunch gazebo_simulator modulidar_gazebo.launch sensor:=velodyne

benwake_farm

ModuLiDAR map cave environment

roslaunch gazebo_simulator modulidar_gazebo.launch sensor:=velodyne world_name:='$(find gazebo_simulator)/worlds/50m_long_mine_world.world' 

benwake_farm

Raspberry pi benchmarking

follow the instructions in sgm_lidar_clustering

SGM clustering Vs lidar_euclidean_cluster_detect

read the benchmarking section in sgm_lidar_clustering

Partners

sigma

Contact us

You might also like...
Collection of quadrupedal robots configured to work in CHAMP development framework

zoo This repository contains configuration packages of various quadrupedal robots generated by CHAMP's setup assistant. Installation You need to have

WoLF: Whole-body Locomotion Framework for quadruped robots

WoLF: Whole-body Locomotion Framework for quadruped robots This package contains the navigation stack to be used with WoLF. Mantainers: Federico Rollo

Let's upgrade cheap off-the-shelf robotic mowers to modern, smart RTK GPS based lawn mowing robots!
Let's upgrade cheap off-the-shelf robotic mowers to modern, smart RTK GPS based lawn mowing robots!

OpenMower Join the Discord server for OpenMower discussion: HERE About the Project ⚠️ DISCLAIMER: IF YOU ARE NOT 100% SURE WHAT YOU ARE DOING, PLEASE

It creates a random word by mixing two English common words into a single one, each one with the first character in capital letter. It also allow you to scroll down infinitely without repeating the same word twice.

startup_namer A new Flutter project. Getting Started This project is a starting point for a Flutter application. A few resources to get you started if

AWS Ambit Scenario Designer for Unreal Engine 4 (Ambit) is a suite of tools to streamline content creation at scale for autonomous vehicle and robotics simulation applications.
AWS Ambit Scenario Designer for Unreal Engine 4 (Ambit) is a suite of tools to streamline content creation at scale for autonomous vehicle and robotics simulation applications.

AWS Ambit Scenario Designer for Unreal Engine 4 Welcome to AWS Ambit Scenario Designer for Unreal Engine 4 (Ambit), a suite of tools to streamline 3D

Hands-On example code for Sensor Fusion and Autonomous Driving Stack based on Autoware
Hands-On example code for Sensor Fusion and Autonomous Driving Stack based on Autoware

Autoware "Hands-On" Stanford Lecture AA274 / Graz University of Technology M. Schratter, J. Zubaca, K. Mautner-Lassnig, T. Renzler, M. Kirchengast, S.

VEX v5 Pro program that records driver movements and plays them back during the autonomous period.

Autonomous Recorder This code was written for team 5588R, but it can be easily modified to work with your team's robot. Notes Code isn't fully finishe

Quake Enhanced mod where one player (The Juggernaut) is very strong and all other players have to kill the Juggernaut

QE Juggernaut Quake Enhanced Juggernaut (A modification of the QEHunter mod by JPiolho.) This is a multiplayer mod where one player is the Juggernaut.

Livox-Mapping - An all-in-one and ready-to-use LiDAR-inertial odometry system for Livox LiDAR
Livox-Mapping - An all-in-one and ready-to-use LiDAR-inertial odometry system for Livox LiDAR

Livox-Mapping This repository implements an all-in-one and ready-to-use LiDAR-inertial odometry system for Livox LiDAR. The system is developed based

Comments
  • Controller Spawner couldn't find the expected controller_manager ROS interface

    Controller Spawner couldn't find the expected controller_manager ROS interface

    Hi, The packages you've done look good. Your list of future features looks even better. I've had a go at running the packages but am running into a few errors. I think this problem finding the expected controller_manager ROS interface might be causing several of the issues. Did you have any of these problems as below so far?

    Thanks Ben

    :~/autobotware_ws$ roslaunch autobotware_simulator robot_navigation.launch sensor:=velodyne world_name:='$(find autobotware_simulator)/worlds/turtlebot3_world.world' map_file:='$(find autobotware_simulator)/maps/map.yaml' ... logging to /home/ben/.ros/log/0e256c5c-b2d7-11eb-929a-30d16b9fbdab/roslaunch-ben-Aspire-2794.log Checking log directory for disk usage. This may take a while. Press Ctrl-C to interrupt Done checking log file disk usage. Usage is <1GB.

    xacro: in-order processing became default in ROS Melodic. You can drop the option. started roslaunch server http://ben-Aspire:46213/

    SUMMARY

    PARAMETERS

    • /LiDAR_topicname: ['/LiDAR1/pcl']
    • /amcl/base_frame_id: robot_footprint
    • /amcl/gui_publish_rate: 50.0
    • /amcl/initial_pose_a: 0.0
    • /amcl/initial_pose_x: 0.0
    • /amcl/initial_pose_y: 0.0
    • /amcl/kld_err: 0.02
    • /amcl/laser_lambda_short: 0.1
    • /amcl/laser_likelihood_max_dist: 2.0
    • /amcl/laser_max_beams: 180
    • /amcl/laser_max_range: 10
    • /amcl/laser_model_type: likelihood_field
    • /amcl/laser_sigma_hit: 0.2
    • /amcl/laser_z_hit: 0.5
    • /amcl/laser_z_max: 0.05
    • /amcl/laser_z_rand: 0.5
    • /amcl/laser_z_short: 0.05
    • /amcl/max_particles: 200
    • /amcl/min_particles: 100
    • /amcl/odom_alpha1: 0.1
    • /amcl/odom_alpha2: 0.1
    • /amcl/odom_alpha3: 0.1
    • /amcl/odom_alpha4: 0.1
    • /amcl/odom_frame_id: odom
    • /amcl/odom_model_type: diff
    • /amcl/recovery_alpha_fast: 0.0
    • /amcl/recovery_alpha_slow: 0.0
    • /amcl/resample_interval: 1
    • /amcl/transform_tolerance: 0.5
    • /amcl/update_min_a: 0.2
    • /amcl/update_min_d: 0.2
    • /gazebo/enable_ros_network: True
    • /joint_state_publisher/use_gui: False
    • /move_base/DWAPlannerROS/acc_lim_theta: 3.2
    • /move_base/DWAPlannerROS/acc_lim_x: 2.5
    • /move_base/DWAPlannerROS/acc_lim_y: 0.0
    • /move_base/DWAPlannerROS/controller_frequency: 10.0
    • /move_base/DWAPlannerROS/forward_point_distance: 0.325
    • /move_base/DWAPlannerROS/goal_distance_bias: 20.0
    • /move_base/DWAPlannerROS/latch_xy_goal_tolerance: False
    • /move_base/DWAPlannerROS/max_scaling_factor: 0.2
    • /move_base/DWAPlannerROS/max_vel_theta: 2.75
    • /move_base/DWAPlannerROS/max_vel_trans: 0.22
    • /move_base/DWAPlannerROS/max_vel_x: 0.22
    • /move_base/DWAPlannerROS/max_vel_y: 0.0
    • /move_base/DWAPlannerROS/min_vel_theta: 1.37
    • /move_base/DWAPlannerROS/min_vel_trans: 0.11
    • /move_base/DWAPlannerROS/min_vel_x: -0.22
    • /move_base/DWAPlannerROS/min_vel_y: 0.0
    • /move_base/DWAPlannerROS/occdist_scale: 0.02
    • /move_base/DWAPlannerROS/oscillation_reset_dist: 0.05
    • /move_base/DWAPlannerROS/path_distance_bias: 32.0
    • /move_base/DWAPlannerROS/publish_cost_grid_pc: True
    • /move_base/DWAPlannerROS/publish_traj_pc: True
    • /move_base/DWAPlannerROS/scaling_speed: 0.25
    • /move_base/DWAPlannerROS/sim_time: 1.5
    • /move_base/DWAPlannerROS/stop_time_buffer: 0.2
    • /move_base/DWAPlannerROS/vth_samples: 40
    • /move_base/DWAPlannerROS/vx_samples: 20
    • /move_base/DWAPlannerROS/vy_samples: 0
    • /move_base/DWAPlannerROS/xy_goal_tolerance: 0.1
    • /move_base/DWAPlannerROS/yaw_goal_tolerance: 0.5
    • /move_base/base_local_planner: dwa_local_planner...
    • /move_base/conservative_reset_dist: 3.0
    • /move_base/controller_frequency: 10.0
    • /move_base/controller_patience: 15.0
    • /move_base/global_costmap/cost_scaling_factor: 3.0
    • /move_base/global_costmap/footprint: [[-0.276, -0.23],...
    • /move_base/global_costmap/global_frame: map
    • /move_base/global_costmap/inflation_radius: 1.0
    • /move_base/global_costmap/map_type: costmap
    • /move_base/global_costmap/observation_sources: scan
    • /move_base/global_costmap/obstacle_range: 3.0
    • /move_base/global_costmap/publish_frequency: 10.0
    • /move_base/global_costmap/raytrace_range: 3.5
    • /move_base/global_costmap/robot_base_frame: robot_footprint
    • /move_base/global_costmap/scan/clearing: True
    • /move_base/global_costmap/scan/data_type: LaserScan
    • /move_base/global_costmap/scan/marking: True
    • /move_base/global_costmap/scan/sensor_frame: coloredLidar
    • /move_base/global_costmap/scan/topic: clusteredPointCLo...
    • /move_base/global_costmap/static_map: True
    • /move_base/global_costmap/transform_tolerance: 0.5
    • /move_base/global_costmap/update_frequency: 10.0
    • /move_base/local_costmap/cost_scaling_factor: 3.0
    • /move_base/local_costmap/footprint: [[-0.276, -0.23],...
    • /move_base/local_costmap/global_frame: odom
    • /move_base/local_costmap/height: 3
    • /move_base/local_costmap/inflation_radius: 1.0
    • /move_base/local_costmap/map_type: costmap
    • /move_base/local_costmap/observation_sources: scan
    • /move_base/local_costmap/obstacle_range: 3.0
    • /move_base/local_costmap/publish_frequency: 10.0
    • /move_base/local_costmap/raytrace_range: 3.5
    • /move_base/local_costmap/resolution: 0.05
    • /move_base/local_costmap/robot_base_frame: robot_footprint
    • /move_base/local_costmap/rolling_window: True
    • /move_base/local_costmap/scan/clearing: True
    • /move_base/local_costmap/scan/data_type: LaserScan
    • /move_base/local_costmap/scan/marking: True
    • /move_base/local_costmap/scan/sensor_frame: coloredLidar
    • /move_base/local_costmap/scan/topic: clusteredPointCLo...
    • /move_base/local_costmap/static_map: False
    • /move_base/local_costmap/transform_tolerance: 0.5
    • /move_base/local_costmap/update_frequency: 10.0
    • /move_base/local_costmap/width: 3
    • /move_base/oscillation_distance: 0.2
    • /move_base/oscillation_timeout: 10.0
    • /move_base/planner_frequency: 5.0
    • /move_base/planner_patience: 5.0
    • /move_base/shutdown_costmaps: False
    • /point_cloud_assembler/odom_frame: odom
    • /point_cloud_assembler/pub_topicname: /assemblerMap
    • /point_cloud_assembler/tf_duration: 0.1
    • /point_cloud_assembler/voxel_size: 0.2
    • /robot_description: <?xml version="1....
    • /rosdistro: melodic
    • /rosversion: 1.14.10
    • /rqt_robot_steering/default_topic: /cmd_vel
    • /sgm_lidar_clustering/LiDAR_topicname: /LiDAR1/pcl
    • /sgm_lidar_clustering/distance_threshold: 0.5
    • /sgm_lidar_clustering/distance_threshold_type: 1.0
    • /sgm_lidar_clustering/ground_segmentation_threshold: 0.2
    • /sgm_lidar_clustering/lidar_max_range: 30.0
    • /sgm_lidar_clustering/max_horizontal_angle: 3.14159
    • /sgm_lidar_clustering/min_horizontal_angle: -3.14159
    • /sgm_lidar_clustering/obj_level_filter_flag: True
    • /sgm_lidar_clustering/obj_level_vol_threshold: 0.1
    • /sgm_lidar_clustering/obj_level_x_max: 2.0
    • /sgm_lidar_clustering/obj_level_x_min: 0.01
    • /sgm_lidar_clustering/obj_level_y_max: 2.0
    • /sgm_lidar_clustering/obj_level_y_min: 0.01
    • /sgm_lidar_clustering/obj_level_z_max: 2.0
    • /sgm_lidar_clustering/obj_level_z_min: 0.1
    • /sgm_lidar_clustering/pub_ma_topicname: clusteredObjectList
    • /sgm_lidar_clustering/pub_pc_topicname: clusteredPointCLoud
    • /skid_steer_bot/hardware_interface/joints: ['left_back_wheel...
    • /skid_steer_bot/joint_state_controller/publish_rate: 50
    • /skid_steer_bot/joint_state_controller/type: joint_state_contr...
    • /skid_steer_bot/mobile_base_controller/angular/z/has_acceleration_limits: True
    • /skid_steer_bot/mobile_base_controller/angular/z/has_velocity_limits: True
    • /skid_steer_bot/mobile_base_controller/angular/z/max_acceleration: 6.0
    • /skid_steer_bot/mobile_base_controller/angular/z/max_velocity: 2.0
    • /skid_steer_bot/mobile_base_controller/base_frame_id: robot_footprint
    • /skid_steer_bot/mobile_base_controller/left_back_wheel: left_back_wheel_h...
    • /skid_steer_bot/mobile_base_controller/left_front_wheel: left_front_wheel_...
    • /skid_steer_bot/mobile_base_controller/linear/x/has_acceleration_limits: True
    • /skid_steer_bot/mobile_base_controller/linear/x/has_velocity_limits: True
    • /skid_steer_bot/mobile_base_controller/linear/x/max_acceleration: 0.6
    • /skid_steer_bot/mobile_base_controller/linear/x/max_velocity: 0.2
    • /skid_steer_bot/mobile_base_controller/pose_covariance_diagonal: [0.001, 0.001, 0....
    • /skid_steer_bot/mobile_base_controller/publish_rate: 50
    • /skid_steer_bot/mobile_base_controller/right_back_wheel: right_back_wheel_...
    • /skid_steer_bot/mobile_base_controller/right_front_wheel: right_front_wheel...
    • /skid_steer_bot/mobile_base_controller/twist_covariance_diagonal: [0.001, 0.001, 0....
    • /skid_steer_bot/mobile_base_controller/type: skid_steer_drive_...
    • /skid_steer_bot/mobile_base_controller/wheel_radius: 0.16
    • /skid_steer_bot/mobile_base_controller/wheel_separation: 0.46
    • /use_sim_time: True

    NODES / amcl (amcl/amcl) gazebo (gazebo_ros/gzserver) gazebo_gui (gazebo_ros/gzclient) joint_state_publisher (joint_state_publisher/joint_state_publisher) map_server (map_server/map_server) move_base (move_base/move_base) point_cloud_assembler (point_cloud_assembler/point_cloud_assembler) robot_state_publisher (robot_state_publisher/robot_state_publisher) rqt_robot_steering (rqt_robot_steering/rqt_robot_steering) rviz (rviz/rviz) rviz_assembler (rviz/rviz) rviz_cluster (rviz/rviz) sgm_lidar_clustering (sgm_lidar_clustering/sgm_lidar_clustering) urdf_spawner (gazebo_ros/spawn_model) /skid_steer_bot/ controller_spawner (controller_manager/spawner) robot_state_publisher (robot_state_publisher/robot_state_publisher)

    auto-starting new master process[master]: started with pid [2817] ROS_MASTER_URI=http://localhost:11311

    setting /run_id to 0e256c5c-b2d7-11eb-929a-30d16b9fbdab process[rosout-1]: started with pid [2829] started core service [/rosout] process[joint_state_publisher-2]: started with pid [2836] process[robot_state_publisher-3]: started with pid [2837] process[gazebo-4]: started with pid [2838] process[gazebo_gui-5]: started with pid [2842] process[urdf_spawner-6]: started with pid [2848] process[sgm_lidar_clustering-7]: started with pid [2849] process[rviz_cluster-8]: started with pid [2855] process[skid_steer_bot/controller_spawner-9]: started with pid [2857] process[skid_steer_bot/robot_state_publisher-10]: started with pid [2858] process[rqt_robot_steering-11]: started with pid [2860] process[point_cloud_assembler-12]: started with pid [2864] process[rviz_assembler-13]: started with pid [2870] process[map_server-14]: started with pid [2872] process[amcl-15]: started with pid [2873] process[move_base-16]: started with pid [2874] process[rviz-17]: started with pid [2879] [ WARN] [1620792231.125411350]: Request for map failed; trying again... initialize obj_level_filter_flag: 1 gnd_seg_threshold: 0.2 distance_threshold: 0.5 point cloud sub topic: /LiDAR1/pcl point cloud pub topic: clusteredPointCLoud object pub topic: clusteredObjectList initialize [ WARN] [1620792231.209772414]: Transformer::setExtrapolationLimit is deprecated and does not do anything topic_names: /LiDAR1/pcl [INFO] [1620792231.443291, 0.000000]: Controller Spawner: Waiting for service controller_manager/load_controller [ INFO] [1620792231.679502515]: Finished loading Gazebo ROS API Plugin. [ INFO] [1620792231.682827108]: waitForService: Service [/gazebo/set_physics_properties] has not been advertised, waiting... [ INFO] [1620792231.775294137]: Finished loading Gazebo ROS API Plugin. [ INFO] [1620792231.777715675]: waitForService: Service [/gazebo_gui/set_physics_properties] has not been advertised, waiting... [INFO] [1620792232.192907, 0.000000]: Loading model XML from ros parameter robot_description [INFO] [1620792232.214761, 0.000000]: Waiting for service /gazebo/spawn_urdf_model [Err] [REST.cc:205] Error in REST request

    libcurl: (51) SSL: no alternative certificate subject name matches target host name 'api.ignitionfuel.org' [WARN] [1620792261.605422, 0.000000]: Controller Spawner couldn't find the expected controller_manager ROS interface. [skid_steer_bot/controller_spawner-9] process has finished cleanly log file: /home/ben/.ros/log/0e256c5c-b2d7-11eb-929a-30d16b9fbdab/skid_steer_bot-controller_spawner-9*.log Error Code: 11 Msg: Unable to find uri[model://turtlebot3_world] [ INFO] [1620792408.824979260]: waitForService: Service [/gazebo/set_physics_properties] is now available. [ INFO] [1620792408.888664318, 0.035000000]: Physics dynamic reconfigure ready. [INFO] [1620792408.943346, 0.087000]: Calling service /gazebo/spawn_urdf_model [ INFO] [1620792409.494303193, 0.200000000]: Camera Plugin: Using the 'robotNamespace' param: '/' [ INFO] [1620792409.501556006, 0.200000000]: Camera Plugin (ns = /) <tf_prefix_>, set to "" Service call failed: transport error completing service call: receive_once[/gazebo/spawn_urdf_model]: DeserializationError cannot deserialize: unknown error handler name 'rosmsg' [ERROR] [1620792419.940837, 0.200000]: Spawn service failed. Exiting. [ INFO] [1620792419.941907352, 0.200000000]: Laser Plugin: Using the 'robotNamespace' param: '/' [ INFO] [1620792419.942079448, 0.200000000]: x:0.000000, y:0.000000,z:0.000000,roll:0.000000,pitch:0.000000,yaw:0.000000 [ INFO] [1620792419.942223790, 0.200000000]: Starting Laser Plugin (ns = /) [ INFO] [1620792419.949228264, 0.200000000]: Laser Plugin (ns = /) <tf_prefix_>, set to "" [ INFO] [1620792420.051874323, 0.200000000]: Starting GazeboRosSkidSteerDrive Plugin (ns = //) [ INFO] [1620792420.089983321, 0.200000000]: Loading gazebo_ros_control plugin [ INFO] [1620792420.090285054, 0.200000000]: Starting gazebo_ros_control plugin in namespace: / [ INFO] [1620792420.091749457, 0.200000000]: gazebo_ros_control plugin is waiting for model URDF in parameter [robot_description] on the ROS param server. [urdf_spawner-6] process has died [pid 2848, exit code 1, cmd /home/ben/catkin_ws/src/AutoOrchards_mower/gazebo_ros_pkgs/gazebo_ros/scripts/spawn_model -x -2 -y 0.5 -Y 0 -urdf -param robot_description -model skid_steer_bot __name:=urdf_spawner __log:=/home/ben/.ros/log/0e256c5c-b2d7-11eb-929a-30d16b9fbdab/urdf_spawner-6.log]. log file: /home/ben/.ros/log/0e256c5c-b2d7-11eb-929a-30d16b9fbdab/urdf_spawner-6*.log [ INFO] [1620792420.230847021, 0.200000000]: Loaded gazebo_ros_control. PointCloud after filtering: 1712 1 before filtering:32768 accumilative filtering:1712 OpenCV Error: Assertion failed (src.type() == CV_8UC1) in findNonZero, file /build/opencv-L2vuMj/opencv-3.2.0+dfsg/modules/core/src/stat.cpp, line 4043 terminate called after throwing an instance of 'cv::Exception' what(): /build/opencv-L2vuMj/opencv-3.2.0+dfsg/modules/core/src/stat.cpp:4043: error: (-215) src.type() == CV_8UC1 in function findNonZero

    PointCloud after filtering: 1707 1 before filtering:32768 accumilative filtering:3181 [sgm_lidar_clustering-7] process has died [pid 2849, exit code -6, cmd /home/ben/autobotware_ws/devel/lib/sgm_lidar_clustering/sgm_lidar_clustering __name:=sgm_lidar_clustering __log:=/home/ben/.ros/log/0e256c5c-b2d7-11eb-929a-30d16b9fbdab/sgm_lidar_clustering-7.log]. log file: /home/ben/.ros/log/0e256c5c-b2d7-11eb-929a-30d16b9fbdab/sgm_lidar_clustering-7*.log PointCloud after filtering: 1698 1 before filtering:32768 accumilative filtering:3727 PointCloud after filtering: 1720 1 before filtering:32768 accumilative filtering:4017

    opened by bj-neilson 2
Releases(0.1.0)
Owner
null
Open source software for autonomous drones.

Prometheus - 自主无人机开源项目 [English Readme] Prometheus是希腊神话中最具智慧的神明之一,希望本项目能为无人机研发带来无限的智慧与光明。 项目总览 Prometheus是一套开源的自主无人机软件平台,为无人机的智能与自主飞行提供全套解决方案。本项目基于PX4

Amov Lab 1.6k Nov 28, 2022
This is official repository of the course Industrial Informatics LT, Year 2021/22, at University of Modena and Reggio Emilia, held at Fondazione Universitaria di Mantova

Industrial informatics LT - Mantova - 2021/22 This is official repository of the course Industrial Informatics LT, Year 2020/21, at University of Mode

High-Performance Real-Time Lab 4 Jun 27, 2022
En este repositorio estaré resolviendo los ejercicios del curso "Fundamentos de Programación" de la carrera Ingeniería Industrial de la Universidad Continental.

Resolviendo Ejercicios en C++ En este repositorio estaré resolviendo los ejercicios del curso "Fundamentos de Programación" de la carrera Ingeniería I

Percy Tuncar 3 Apr 29, 2022
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open

Microsoft 13.7k Nov 25, 2022
CARLA is an open-source simulator for autonomous driving research.

CARLA is an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems.

CARLA 8.5k Nov 19, 2022
An Open-source Strong Baseline for SE(3) Planning in Autonomous Drone Racing

Fast-Racing An Open-source Strong Baseline for SE(3) Planning in Autonomous Drone Racing 0. Overview Fast-Racing is a strong baseline that focuses on

ZJU FAST Lab 104 Nov 17, 2022
An open autonomous driving platform

We choose to go to the moon in this decade and do the other things, not because they are easy, but because they are hard. -- John F. Kennedy, 1962

Apollo Auto 21.9k Nov 25, 2022
Otto-SetupAssist provides an Arduino sketch which assist you to build Otto robots.

Otto-SetupAssist Otto-SetupAssist provides an Arduino sketch which assist you to build Otto robots. This sketch provides two features: Move servos to

ROBOT.ICHIBA 1 Oct 20, 2021
Local Navigation Planner for Legged Robots

ANYmal Rough Terrain Planner Sampling based path planning for ANYmal, based on 2.5D height maps. More detailed instructions still to come. The paper d

Robotic Systems Lab - Legged Robotics at ETH Zürich 34 Nov 17, 2022
Wolf_descriptions - WoLF: Whole-body Locomotion Framework for quadruped robots

WoLF: Whole-body Locomotion Framework for quadruped robots This repo contains a collection of different robots and sensors used in WoLF. Setup See the

Gennaro Raiola 7 Oct 6, 2022